A control method facilitates human control over natural and engineered mechanisms in order to regulate, command, direct and modify the behavior of these mechanisms.
The mechanism to be controlled is called the "plant". A plant is controllable when one or more known inputs to the plant can be manipulated in order to obtain consistent and predictable changes in one or more outputs of the plant. Unknown inputs to the plant have only minor effects on the controlled outputs and other outputs of the systems have only minor side effects on the environment. Controllers are required because the manipulated inputs usually are not suitable to accept the desired commands. These techniques are embodied in the mechanism known as "control systems" or "controllers".
The control systems are additions to the plants and the combination may be called a controlled system. The entire controlled system may be regarded as a signal follower system where desired output signals should be followed, with a certain degree of fidelity, by the controlled outputs in time, direction and magnitude. The physical type and dimensions of the desired output signal and the controlled output may or may not be the same. In general, the controlled output is related to the desired output by a proportionality constant which may be dimensionless or, usually, serve also as a dimensional conversion factor between the desired output and the controlled output.
Various types of control systems are known. The simple open loop control systems of the prior art include a desired output signal as input to a controller. The controller includes a mathematical model of the controlled system and defines the relationship between the desired output signal and the required manipulated input to the plant. The controller also includes means to generate the correct type and magnitude of the manipulated input signal. The manipulated input signal is directly applied to the plant which, in turn, produces the controlled output. The simple open loop system is shown on FIG. 1. Accuracy of this system primarily depends on the correctness of the control model. In general, the open loop systems tend to provide rapid response to changes in the desired output.
A control system using feedback takes into account the effect of the actual controlled system on the system input and can develop an error to correct variations of the actual system output from the desired system output. However, attempts to make such corrections can lead to dynamic problems due to instability and system response time.
The simple feedback control systems of the prior art have a feedback sensor that measures the current value of the controlled output. The feedback signal is converted to have the same physical units as the desired output signal. Both the desired output signal and the actual output feedback signal are applied to a comparator which generates an output error signal as the difference between the two signals. The error signal is the input to the controller. The controller includes an algorithm which computes values for the manipulated input to the plant proportional to the error signal or to some time dependent function of the error signal. The factor of proportionality is known as the system gain. The controller also includes means to generate the actual manipulated input. The manipulated input is directly applied to the plant which, in turn, generates the controlled output.
Accuracy of the feedback control systems fundamentally depends on the accuracy of the feedback sensor. It also depends on proper selection of the gain factor and the error function according to characteristics of the plant and the frequency domain of the desired output.
One disadvantage of the closed loop system is the time dependency of the system accuracy. The feedback signal, if improperly applied or if the feedback loop includes time delay, may induce system output instabilities and phase shifts between the desired and the actual output. Proper system stability usually necessitates reduction of the speed of system response to time variable desired output signals. This results in additional errors under dynamic operating conditions.
Since the signal path includes a closed loop, these systems are also known as closed loop sysytems. A diagram of a basic closed-loop feedback control system is illustrated on FIG. 2. The basic idea of this system is to make the manipulated input to be a function of the output error so that a greater error causes an automatic increase of the manipulated input. This tends to decrease the error between the desired output and the controlled output. One method involves change of the manipulated which generates an output error signal as the difference between the two signals. The error signal is the input to the controller. The controller includes an algorithm which computes values for the manipulated input to the plant proportional to the error signal or to some time dependent function of the error signal. The factor of proportionality is known as the system gain. The controller also includes means to generate the actual manipulated input. The manipulated input is directly applied to the plant which, in turn, generates the controlled output.
Accuracy of the feedback control systems fundamentally depends on the accuracy of the feedback sensor. It also depends on proper selection of the gain factor and the error function according to characteristics of the plant and the frequency domain of the desired output.
One disadvantage of the closed loop system is the time dependency of the system accuracy. The feedback signal, if improperly applied or if the feedback loop includes time delay, may induce system output instabilities and phase shifts between the desired and the actual output. Proper system stability usually necessitates reduction of the speed of system response to time variable desired output signals. This results in additional errors under dynamic operating conditions.
Since the signal path includes a closed loop, these systems are also known as closed loop systems. A diagram of a basic closed-loop feedback control system is illustrated on FIG. 2. The basic idea of this system is to make the manipulated input to be a function of the output error so that a greater error causes an automatic increase of the manipulated input. This tends to decrease the error between the desired output and the controlled output. One method involves change of the manipulated input proportionally to the time integral of the output error. In this system, the output error continually decreases and becomes negligible after a suitable period when constant output is demanded. The general purpose of the closed loop control systems is to improve the control accuracy beyond the capability of open loop systems or obtain control when an open loop model cannot be used.
These known control methods are disadvantageous in that they cannot maintain a rapid response while compensating for the variation in plant characteristics over time and the variation in individual plant characteristics caused by manufacture.
The prior art also developed hybrid systems in order to approach a combination of the advantages of both the open loop and the closed loop feedback control systems. These systems of the prior art may be classified as global feedback hybrid systems. In this system, an approximate value of the manipulated input is computed by an open loop control model from the magnitude of the desired output. The final magnitude of the manipulated input is typically computed as the sum of the open loop estimated value and a global feedback correction value which is generated by a closed loop system similarly to the methods applied in the simple closed loop systems. The block diagram of the global feedback or hybrid control system is shown on FIG. 3.
Advantages of the global feedback hybrid systems include fast system response within the accuracy of the open loop model and high closed loop accuracy when the desired output is only slowly variable.
Inherent problems of the global feedback hybrid systems are open loop errors with highly variable desired outputs and susceptibility to closed loop instabilities.
The prior art includes externally adaptive versions of the above control system types. In the externally adaptive open loop systems, the control model is a function of input variables provided by additional input sensors. In the externally adaptive feedback system, the system gain is calculated as a function of input variables. In the externally adaptive global feedback hybrid systems, both the control model and the system gain may be functions of input variables.
An externally adaptive hybrid control system with additional global feedback correction is shown in FIG. 4 which illustrates the use of external adaptive features both in the open loop model and in the feedback system gain factor.
Alternate adaptive methods have been applied by the prior art in feedback control systems in order to further improve the speed of response based on previous experiences of the system. An example of a simple internally adaptive feedback system is shown in FIG. 5.
The internally adaptive method of the prior art is a global self correcting method. The multidimensional operating space as defined by the desired input and the major input variables is divided up into incremental cells. Each one of the cells is assigned to a memory location in the control computer. During normal operation of the feedback or hybrid systems, the global feedback corrections attained while the system operates for a suitable time period within the range of each cell are saved in the memory locations assigned to the cells. After suitable period of operation, the memory of a number of cells are filled with the latest corrections that have been previously provided by the feedback. Memory location of cells which have not been reached previously by the system have zero initial correction values.
As the system continues to operate and enters the region of a previously updated cell, the previously used global correction value is recovered and used as an additive--quantity to the current global feedback correction. Usually, the previous global correction is adequate and the feedback provides zero additional correction. The feedback correction will be other than zero if a drift occurred in the calibration of the system component. Upon leaving the cell, the sum of the previous correction and the current feedback correction is stored in the cell memory. This insures that the correction memory is continuously updated.
The same principles of the internally adaptive self correcting method can also be applied to hybrid systems. An example of this application is shown in FIG. 6. The self correcting internally adaptive systems operate with improved fidelity without substantial time delays that would occur if only feedback correction was available and without the open loop model errors provided that the correction memory cells are suitably filled and updated. The fast system response is obtained because the system converts itself into a highly corrected open loop controller after the self correction takes place since the closed loop is practically inactive and it merely updates the error memories for slow drifts in the components.
A disadvantage of this self correcting method is that usually a large error memory is required in order to ensure sufficient table resolution. The required period of error data correction is relatively long because portions of the logged error can be incorrect, interpollation between the error cells or across unfilled regions is not well defined and requires substantial software. Extrapolation of the error data into unfilled cells is difficult and the update of already filled cells tends to be slow.
The self-correcting method is most appropriate when a satisfactory mathematical control model of the plant is not available. Then the error memory provides the functions of an open loop model in feedback systems and it supplements the inadequacies of the control model in hybrid systems. However, the system inputs should sweep through their entire range of operation frequently in order to suitably update the error memory.